Hire an AI ad comparison test reviewer

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• A test plan with one difference, a code for each version and the audience size needed
• A reply offer, identical in both versions, with the lines to use
• A winner rule written before launch, with a read date
• After the test, the gap as a percentage, a luck check and a keep, rerun or stop call
• A record of what the test taught and the next test to run

How it does the job well

• Write for one named audience and one action. Each asset has a single job.
• Use the customer's own words from reviews, calls or surveys before inventing language.
• Every claim needs proof the business can show. Leave unproven claims out or mark them.
• Judge results against the business goal, such as profit or qualified leads, not clicks alone.

Mistakes it avoids

• Generic copy that could fit any brand.
• Comparing periods or campaigns that are not comparable, such as different dates, budgets or tracking.
• Calling a test winner before there is enough data.

What a good result looks like

An example, not your task: You have two ads, emails or pages and want to know which sells more before you put money behind one.

• Step 1: Fair split-run test plan. The one difference, what stays equal, a code for each version, the audience needed and the winner rule.
• Step 2: Reply offer. A small offer, the same in both versions, with the ad line, reply form and thank-you lines.
• Pause. You run both versions at the same time and count replies and sales by code.
• Step 3: The result. The gap as a percentage, a luck check, a fairness check, cost per reply and sale, and a keep, rerun or stop call.
• Lesson record and next test. What the test taught, with the date and audience, and the next test to run.
• Hand-back summary. Each step's file and every MISSING line in one list.

How the work is checked

• Each step passed its own checks, or the run stopped at the step that failed and says why.
• The steps ran in order, and each one used the result of the one before.
• Nothing was invented to fill a gap. Every gap is a MISSING: line.
• Nothing was sent, published or paid for without a clear yes.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

A second opinion

Before it hands back, your AI reviews the draft the way John Caples and Claude Hopkins would. This is a way of reviewing the work. It does not mean they wrote or endorse it.

Capabilities

• Plan a fair split-run test. Finds every difference between the versions and narrows the test to one. Splits the audience into matched halves, gives each version a code and sets the reply target and winner rule before launch.
• Set a reply offer that brings enough replies. Picks a small free or low-cost item that relates to what you sell, decides whether to show or hide it and compares expected replies with the target. The offer is the same in both versions.
• Run the test. A pause. You run both versions at the same time and count replies and sales by code.
• Read the result. States the gap as a percentage, checks it against luck, checks the test stayed fair and follows replies through to sales and cost. Ends with keep, rerun or stop, a lesson record and the next test.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id ad-ab-test only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/ad-ab-test/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• The two versions of the ad, email or page
• Your offer and what a reply means (optional)
• Your product facts, so a reply item can be chosen (optional)
• Time to run the test and count replies by version

Helpful context (optional)

• Your usual reply rate for each channel
• The size of the audience you can reach with each version
• Your record of past tests

Tools and access

• Your email tool or ad platform: Most have an even split option and export counts by code.
• A spreadsheet: Holds the codes, counts and read dates for every test.
• Your email tool or ad platform: Most have an even split option that does the halves for you.
• A spreadsheet: Holds the keys, counts and read dates for every test in one place.
• Claude, ChatGPT or Gemini: Listing options and weighing them is text work any strong chat AI handles with this skill.
• A spreadsheet: Tracks replies, buyers and cost per piece for each item.
• A spreadsheet: Holds the counts and gives the audience and reply sums.
• Your email tool or ad platform: Exports counts by version key.

Functions and deliverables

• Ad comparison test reviewer: Plan a fair comparison, draft the same reply offer for both ads and read your results with a keep, rerun or stop call.
  • A test plan with one difference, a code for each version and the audience size needed
  • A reply offer, identical in both versions, with the lines to use
  • A winner rule written before launch, with a read date
  • After the test, the gap as a percentage, a luck check and a keep, rerun or stop call
  • A record of what the test taught and the next test to run
• A/B test design planner: Plan a fair split-run test of two ads, emails or pages. Get one change, a key on each, the audience size and a winner rule.
  • The one difference being tested
  • What must stay equal and how the audience is split
  • A key (code) for each version
  • The audience size needed, with the sum shown
  • A winner rule with a read date, plus a plan for more than two versions
  • The traps to avoid
• Ad response incentive planner: Pick one reply offer for your ad test that brings enough replies from real buyers. Get the offer lines and a boost plan.
  • A chosen reply offer and a back-up, with the cost per piece
  • A decision on shown or hidden, and a screen if one is needed
  • Expected replies against your target, and the order of boosts if short
  • The offer lines, with the condition next to any "free"
  • A note on how to match replies to buyers later
• A/B test results reader: Read your split-run test results: see how much better one version is, whether luck explains it, and get a keep, rerun or stop call.
  • A table of both versions and the gap as a percentage
  • A luck check with the sum shown
  • Sales per hundred replies and cost per reply and per sale
  • A keep, rerun or stop call with its reason
  • A record of what the test taught, and the next test to run
• Brand profile builder: Share your website. Get a reusable profile covering your products, customers, voice and approved claims, with sources.
  • A folder of eight plain files, from a start file for your AI to a claims list and a change log
  • A tag on every fact, and every claim marked approved, pending or banned
  • A two-sentence diagnosis of your biggest gap, and a list of what's missing and who can answer it
  • A short slice for your next step, if you name one
• John Caples: Write headlines and plan a fair ad test through John Caples’s recorded approach. Lead with the reader’s gain and count replies by version.
  • Your problem worked on the way John Caples would: their questions, their method, their push-back
  • The answer or the work, in John Caples's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step
• Claude Hopkins: Write specific ads or plan a small buyer test using Claude Hopkins’s recorded approach. Replace vague praise with facts and track cost per customer.
  • Your problem worked on the way Claude Hopkins would: their questions, their method, their push-back
  • The answer or the work, in Claude Hopkins's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step

Tasks you can use it for

• You have two ads, emails or pages and want to know which sells more before you put money behind one.
• A past test gave a result nobody trusted.
• You can send each version to a few thousand people, or run both at the same time on a platform.

Limits to check before starting

• You have one ad and nothing to compare it with: check it with the Ad response copy editor, or ask a customer to read it.
• You only want to know if an ad's meaning lands: use the Ad meaning test planner.
• Your channel cannot split an audience evenly or run both at once: compare before and after with the Ad change decision checker.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Download the handoff pack. It's a zip with HANDOFF.md and every skill file this workflow uses.
• Give the folder to Claude (in Claude Code, or as files in a Claude Project) and say "Follow HANDOFF.md".
• Give it both versions, your usual reply rate and the audience you can reach.
• It plans the test and the reply offer. Put the same offer lines and the codes into both versions and launch them together.
• When the read date arrives, count replies and sales by code and bring the counts back for step 3.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/ad-ab-test for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.